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At least 73 records · Page 4

Introduction to Aircraft Icing and NASA's Approach to Understanding It

This presentation provides an introduction to aircraft icing and describes NASA’s approach to understanding it. The presentation covers various topics on icing. A general overview of different types of icing is provided, which includes airframe icing, jet engine icing, and rotorcraft icing. The presentation discusses NASA’s approach to studying the various forms of aircraft icing, which includes conducting flight tests, performing ground-based icing wind tunnel tests, and developing computational tools that simulate the icing physics. An overview on the future of aviation and icing is provided. The presentation is largely high level, but also provides some technical icing physics discussion.

Aircraft Icing↗

High-resolution Hindcasts for U.S. Wave Energy Resource Characterization

The marine and hydrokinetic (MHK) industry is at an early stage of development and has the potential to play a significant role in diversifying the U.S. energy portfolio and reducing the U.S. carbon footprint. Wave energy is the largest among all the U.S. MHK energy resources, which include wave energy, ocean current, tidal-instream, ocean thermal energy conversion, and river-instream. Wave resource characterization is an essential step for regional wave energy assessments, Wave Energy Converter (WEC) project development, site selection and WEC design. The present paper provides an overview of a joint modelling effort by the Pacific Northwest National Laboratory and Sandia National Laboratories on high-resolution wave hindcasts to support the U.S. Department of Energy’s Water Power Technologies Office’s program of wave resource characterization, assessment and classifications in all US coastal regions. Topics covered include the modelling approach, model input requirements, model validation strategies, high performance computing resource requirements, model outputs and data management strategies. Examples of model setup and validation for different regions are provided along with application to development of classification systems, and analysis of regional wave climates. Lessons learned and technical challenges of the long-term, high-resolution regional wave hindcast are discussed.

Yang, Zhaoqing↗

ExaWind: Opportunity for Discovery

The predictive simulation of the dynamics of modern wind turbines and wind farms is a high-performance-computing (HPC) grand challenge. Modern wind turbines are the largest rotating machines in the world, with rotor diameters exceeding 200 meters, and with heights well into the atmospheric boundary layer. To address this grand challenge, the U.S. Department of Energy (DOE) Wind Energy Technologies Office and the Exascale Computing Project have been supporting the creation of the ExaWind modeling and simulation environment since 2016. ExaWind is composed of the incompressible-flow computational-fluid-dynamics (CFD) solvers AMR-Wind and Nalu-Wind and the wind-turbine-dynamics solver OpenFAST. In our hybrid CFD approach, Nalu-Wind unstructured-grid models resolve the near-body flow around the turbine; those models are embedded in, and two-way coupled to, an AMR-Wind structured-grid mesh through overset meshes. In this talk I give an overview of ExaWind software stack and describe how it is being used to address important problems in wind energy.

computational fluid dynamics↗

Large-Scale Computational Fluid Dynamics Simulations of Aerospace Configurations on the Frontier Exascale System

Over the past fifteen years, the high performance computing landscape has undergone a seismic shift in both hardware and software paradigms, which has been necessary to realize a 1000× leap in computational performance while meeting stringent constraints on power consumption. A historical overview of a long-term research effort aimed at addressing these challenges within the context of a commonly-used aerospace computational fluid dynamics (CFD) application is presented. Details of the current implementation as they relate to the new era of exascale-relevant hardware architectures and programming models are described. Two large-scale simulations of aerospace configurations are performed using the entire Frontier exascale system, currently ranked as the most powerful supercomputing system in the world. The effort serves to address a 2024 milestone posed a decade ago by the seminal CFD Vision 2030 Study.

Eric J Nielsen↗

Acceleration of the particle-in-cell code Osiris with graphics processing units

Fully relativistic particle-in-cell (PIC) simulations are crucial for advancing our knowledge of plasma physics. Modern supercomputers based on graphics processing units (GPUs) offer the potential to perform PIC simulations of unprecedented scale, but require robust and feature-rich codes that can fully leverage their computational resources. In this work, this demand is addressed by adding GPU acceleration to the PIC code Osiris. An overview of the algorithm, which features a CUDA extension to the underlying Fortran architecture, is given. Detailed performance benchmarks for thermal plasmas are presented, which demonstrate excellent weak scaling on NERSC's Perlmutter supercomputer and high levels of absolute performance. The robustness of the code to model a variety of physical systems is demonstrated via simulations of Weibel filamentation and laser-wakefield acceleration run with dynamic load balancing. Finally, measurements and analysis of energy consumption are provided that indicate that the GPU algorithm is up to ~14 times faster and ~7 times more energy efficient than the optimized CPU algorithm on a node-to-node basis. The described development addresses the PIC simulation community's computational demands both by contributing a robust and performant GPU-accelerated PIC code and by providing insight into efficient use of GPU hardware.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Full Detector Simulation with Unprecedented Background Occupancy at a Muon Collider

In recent years, a Muon collider has attracted a lot of interest in the high-energy physics community, thanks to its ability of achieving clean interaction signatures at multi-TeV collision energies in the most cost-effective way. Estimation of the physics potential of such an experiment must take into account the impact of beam-induced background on the detector performance, which has to be carefully evaluated using full detector simulation. Tracing of all the background particles entering the detector region in a single bunch crossing is out of reach for any realistic computing facility due to the unprecedented number of such particles. To make it feasible a number of optimisations have been applied to the detector simulation workflow. This contribution presents an overview of the main characteristics of the beam-induced background at a Muon collider, the detector technologies considered for the experiment and how they are taken into account to strongly reduce the number of irrelevant computations performed during the detector simulation. Special attention is dedicated to the optimisation of track reconstruction with the conformal tracking algorithm in this high-occupancy environment, which is the most computationally demanding part of event reconstruction.

97 MATHEMATICS AND COMPUTING↗

NREL HPC FY23 Allocation Webinar

This is an overview of the EERE and NREL HPC allocation process designed to help users submit requests in an effective manner.

Eagle↗

Computational structural mechanics methods research using an evolving framework

Advanced structural analysis and computational methods that exploit high-performance computers are being developed in a computational structural mechanics research activity sponsored by the NASA Langley Research Center. These new methods are developed in an evolving framework and applied to representative complex structural analysis problems from the aerospace industry. An overview of the methods development environment is presented, and methods research areas are described. Selected application studies are also summarized.

Knight, N. F., Jr.↗

Hybrid-VPIC: An open-source kinetic/fluid hybrid particle-in-cell code

Hybrid-VPIC is an extension of the open-source high-performance particle-in-cell (PIC) code VPIC incorporating hybrid kinetic ion/fluid electron solvers. This paper describes the models that are available in the code and gives an overview of applications of the code to space and laboratory plasma physics problems. Particular choices in how the hybrid solvers were implemented are documented for reference by users. A few solutions for handling numerical complications particular to hybrid codes are also described. Finally, special emphasis is given to the computationally taxing problem of modeling mix in collisional high-energy-density regimes, for which more accurate electron fluid transport coefficients have been implemented for the first time in a hybrid PIC code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

FENIX: Towards a Fully Integrated Multiphysics Framework for Plasma Facing Component Modeling

Computational tools have a crucial role to play in accelerating the deployment of fusion as a clean, reliable, abundant, and sustainable energy source. Multiphysics, high-fidelity simulation capabilities can help model, study, and predict intricate interactions between materials performance, plasma exposure, neutron irradiation, and engineering processes. As such, they can assist in the resolution of scientific and engineering challenges underpinning design, construction, and commission of fusion power plants. To address these needs, ongoing efforts are leveraging the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework and delivering new computational tools for the fusion community. These tools inherit crucial attributes from MOOSE. They are open-source, modular, integrated with nuclear industry-standard software quality assurance processes, and enable multiphysics, multi-fidelity, fully integrated, zero- to three-dimensional, and massively parallel simulations. After a short overview of these capabilities, we will present the development of Fusion ENergy Integrated multiphys-X (FENIX), a MOOSE-based application designed to enable plasma facing component design and performance evaluation. Throughout their lifetime, plasma facing components are exposed to extreme thermal loads, repeated thermal shocks, and irradiation by plasma ions, neutral particles, and high-energy neutrons. Consequently, designing a plasma facing component with acceptable lifetime degradation is extremely challenging. FENIX aims to model the multiphysics environment in which plasma facing components evolve to accelerate their design studies. To that end, FENIX couples existing MOOSE capabilities such as heat transfer, thermomechanics, and thermal hydraulics, with tritium transport via the MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8), with neutronics via the MOOSE-based high-fidelity neutron-photon transport and fluid dynamics code Cardinal, and finally with Particle-in-Cell plasma simulation capabilities being developed in this project. In this study, we present the current FENIX capabilities and preliminary results of its application to model the Tritium Plasma Experiment set up at Idaho National Laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Application of advanced computational technology to propulsion CFD

The Internal Fluid Mechanics Division of the NASA Lewis Research Center is combining the key elements of computational fluid dynamics, aerothermodynamic experiments, and advanced computational technology to bring internal computational fluid dynamics (ICFM) to a state of practical application for aerospace propulsion system design. This paper presents an overview of efforts underway at NASA Lewis to advance and apply computational technology to ICFM. These efforts include the use of modern, software engineering principles for code development, the development of an AI-based user-interface for large codes, the establishment of a high-performance, data communications network to link ICFM researchers and facilities, and the application of parallel processing to speed up computationally intensive and/or time-critical ICFM problems. A multistage compressor flow physics program is cited as an example of efforts to use advanced computational technology to enhance a current NASA Lewis ICFM research program.

Szuch, John R.↗

NASA’s Rotating Detonation Rocket Engine Development

The Rotating Detonation Rocket Engine has maintained steady development at NASA with many staggering performance advantages demonstrated to date over the state-of-the-art (SOA). The implementation of additive manufacturing and specialized NASA developed alloys have enabled rapid maturation of the technology. Several hot fire test projects have been successfully conducted at Marshall Space Flight Center under an early career initiative project funded by NASA Space Technology Mission Directorate. In addition, a new start Technology Demonstration Mission (TDM) project has been funded to investigate challenges relating to integration of turbomachinery with an RDRE thrust chamber assembly. This engine system demonstration will leverage a methane/oxygen single shaft turbopump with fuel rich gas generator and a 10,000 lbf thrust chamber assembly. The configuration was down selected based on feedback from both US industry collaborators and power balance trades in combination with technical feasibility. To date, industry has identified several use cases for RDRE ranging from thruster to primary launch vehicle propulsion. A wide range of fuel and oxidizers were also identified including but not limited to Methane, Kerosene and other liquid hydrocarbon (LH) fuels, and hydrogen. Recent work at NASA and in partnership with NASA has investigated these major fuels of interest with oxygen, air, and hydrogen peroxide (HTP) for various applications. NASA Marshall has already investigated the use of hydrogen/oxygen, methane/oxygen, kerosene/oxygen, and has plans in partnership with industry and academia to investigate LH/air and LH/HTP. In addition to propellants, hardware geometry has been investigated with some critical lessons learned toward greater theoretical performance over the SOA. To this end, several experimental and computational activities are ongoing to further advance the RDRE towards flight missions. Given the rate of advancement, it is highly likely the technology will be flown in space mission in the coming decade. This work documents and overviews many of these investigations and overviews NASA’s future plans for the technology maturation.

Thomas Teasley↗

Application of advanced computational technology to propulsion CFD

The Internal Fluid Mechanics Division of the NASA Lewis Research Center is combining the key elements of computational fluid dynamics, aerothermodynamic experiments, and advanced computational technology to bring internal computational fluid dynamics (ICFM) to a state of practical application for aerospace propulsion system design. This paper presents an overview of efforts under way at NASA Lewis to advance and apply computational technology to ICFM. These efforts include the use of modern, software engineering principles for code development, the development of an AI-based user-interface for large codes, the establishment of a high-performance, data communications network to link ICFM researchers and facilities, and the application of parallel processing to speed up computationally intensive and/or time-critical ICFM problems. A multistage compressor flow physics program is cited as an example of efforts to use advanced computational technology to enhance a current NASA Lewis ICFM research program.

Szuch, John R.↗

Petaflops Computing: The Key Algorithmic Challenges

The prospect of petaflops-class computers brings to the fore some important algorithmic issues that have been considered in the high performance computing community for several years. Key among them are (1) concurrency (whether the fundamental concurrency of an algorithm is sufficient to keep thousands of processors productively busy); (2) data locality; (3) latency tolerance; and (4) memory and operation count scaling. This introductory presentation will give an overview of these issues.

Bailey, David H.↗

Charon Message-Passing Toolkit for Scientific Computations

Charon is a library, callable from C and Fortran, that aids the conversion of structured-grid legacy codes-such as those used in the numerical computation of fluid flows-into parallel, high- performance codes. Key are functions that define distributed arrays, that map between distributed and non-distributed arrays, and that allow easy specification of common communications on structured grids. The library is based on the widely accepted MPI message passing standard. We present an overview of the functionality of Charon, and some representative results.

VanderWijngaart, Rob F.↗

Bridging the Gap from Networking Technologies to Applications: Workshop Report

The objective of the Next Generation Internet (NGI) Federal program is threefold, encompassing development of networking technologies, high-performance network testbeds, and revolutionary applications. There have been notable advances in emerging network technologies and several nationwide testbeds have been established, but the integration of emerging technologies into applications is lagging. To help bridge this gap between developers of NGI networking technologies and developers of NGI applications, the NASA Research and Education Network (NREN) project hosted a two-day workshop at NASA Ames Research Center in August 1999. This paper presents a summary of the results of this workshop and also describes some of the challenges NREN is facing while incorporating new technologies into HPCC and other NASA applications. The workshop focused on three technologies - Quality of Service (QoS), advanced multicast, and security-and five major NGI application areas - telemedicine, digital earth, digital video, distributed data-intensive applications, and computational infrastructure applications. Network technology experts, application developers, and NGI testbed representatives came together at the workshop to promote cross-fertilization between the groups. Presentations on the first day, including an overview of the three technologies, application case studies and testbed status reports, laid the foundation for discussions on the second day. The objective of these latter discussions, held within smaller breakout groups, was to establish a coherent picture of the current status of the various pieces of each of the three technologies, to create a roadmap outlining future technology development, and to offer technological guidance to application developers. In this paper we first present a brief overview of the NGI applications that were represented at the workshop, focusing on the identification of technological advances that have successfully been incorporated in each application and technological challenges that remain. Next we present the technology roadmaps that were created at the workshop, summarizing the status of various mechanisms that are currently under development and forecasting when various advances are likely to occur within the next one-to-three-year time span. Then we identify issues that were raised at the workshop that might hinder technology development or that might impede integration into NGI applications. We also report some specific guidelines that were offered at the workshop to enable application developers to integrate and effectively use emerging NGI technology building blocks. Finally, we describe NREN activities to incorporate emerging technologies into NASA applications. These activities include support for other NASA High-Performance Computing and Communications Program areas such as IPG (Information Power Grid), support for NASA science enterprises such as Earth science and Mars program prototyping activities, support for satellite/terrestrial networking applications such as the TransAtlantic and TransPacific demonstrations and the Interplanetary Internet, support for NASA telemedicine applications such as the Virtual Collaborative Clinic, and participation in NGI advanced technology testbed initiatives such as the QBone and the NTON/Supernet. For each activity we highlight the primary technological challenge that is associated with it.

Johnson, Marjory J.↗

Quantum computing for nuclear physics

Future quantum computers are anticipated to be able to perform simulations of quantum many-body systems and quantum field theories that lie beyond the capabilities of classical computation. This will lead to new insights and predictions for systems ranging from dense non-equilibrium matter, to low-energy nuclear structure and reactions, to high-energy collisions. I present an overview of digital quantum simulations in nuclear physics, with select examples relevant for studies of quark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey

Uncertainty quantification (UQ) includes the characterization, integration, and propagation of uncertainties that result from stochastic variations and a lack of knowledge or data in the natural world. Monte Carlo (MC) method is a sampling-based approach that has widely used for quantification and propagation of uncertainties. However, the standard MC method is often time-consuming if the simulation-based model is computationally intensive. This article gives an overview of modern MC methods to address the existing challenges of the standard MC in the context of UQ. Specifically, multilevel Monte Carlo (MLMC) extending the concept of control variates achieves a significant reduction of the computational cost by performing most evaluations with low accuracy and corresponding low cost, and relatively few evaluations at high accuracy and corresponding high cost. Multifidelity Monte Carlo (MFMC) accelerates the convergence of standard Monte Carlo by generalizing the control variates with different models having varying fidelities and varying computational costs. Multimodel Monte Carlo method (MMMC), having a different setting of MLMC and MFMC, aims to address the issue of UQ and propagation when data for characterizing probability distributions are limited. Multimodel inference combined with importance sampling is proposed for quantifying and efficiently propagating the uncertainties resulting from small data sets. All of these three modern MC methods achieve a significant improvement of computational efficiency for probabilistic UQ, particularly uncertainty propagation. Finally, an algorithm summary and the corresponding code implementation are provided for each of the modern MC methods. The extension and application of these methods are discussed in detail.

97 MATHEMATICS AND COMPUTING↗